Abstract

Autonomous vehicles offer many potential benefits; however, this expansion of cyber-physical systems also introduces a new potential vulnerability through cybersecurity threats. It is therefore important to understand the role vehicle occupants can play in preventing and responding to cyberattacks. The objective of this study is to (1) evaluate drivers’ responses to unexpected cyberattacks, and (2) evaluate how cybersecurity knowledge affects situation awareness (SA) during cyberattacks on automated driving. A driving simulator study with 20 participants was conducted to measure drivers’ performance during unexpected cyberattacks on a SAE Level 2 partially-autonomous vehicle and the infrastructure in the driving environment. Each participant experienced four driving scenarios, each scenario with a different cyberattack. Two cyberattacks were directly on the vehicle and two were on the infrastructure. Situation Awareness Global Assessment Technique (SAGAT) was used to measure participants’ situation awareness during the drives and at the time of the cyberattacks. Participant takeover responses to the cyberattacks were collected through the driving simulator. Participants also completed a cybersecurity knowledge survey at the end of the experiment to assess their previous overall cyber awareness and experience with autonomous vehicles. Most of the participants recognized the cyberattacks, however only about half of the participants chose to takeover control of the vehicle during the attacks, and in one attack no one overtook the automation. Results from ANOVAs showed significantly higher SA for participants with greater familiarity with cybersecurity terms and vehicle-to-everything technology. In addition, SA scores were significantly higher for participants who believed security systems (i.e., firewall, encryption) are important and for those who felt protected against cybercrimes. The present results suggest that increased cybersecurity knowledge can cause a high level of situation awareness during automated driving, which can help drivers to control unexpected driving situations due to cybersecurity attacks.

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